A system according to one embodiment includes an automatic gain control circuit configured to provide an amplifier gain value; a temperature sensing circuit configured to provide a temperature; an antenna switching circuit configured to decouple an antenna from the receiver during a noise figure calibration interval; a signal power measurement circuit configured to measure input power to the receiver; a noise figure estimation circuit configured to estimate a receiver noise figure during the noise figure calibration interval based on an initial receiver noise variance, the temperature and the amplifier gain value, wherein the initial receiver noise variance is estimated based on the measured input power during the noise figure calibration interval; and a noise variance tracking circuit configured to calculate updated estimates of the receiver noise variance, wherein the updated estimates are based on updates of the measured temperature and updates of the measured amplifier gain.

Embodiments of the present disclosure provide a method and apparatus for determining a nonlinear characteristic and a system. The method for determining a nonlinear characteristic includes: determining a correction factor of a nonlinear item of a nonlinear model of a system to be measured according to an input and/or a parameter of the system to be measured; correcting the nonlinear item of a nonlinear model of the system to be measured by using the correction factor; and obtaining a nonlinear characteristic of the system to be measured according to the corrected nonlinear model. The nonlinear characteristic allows the input and/or the parameter of the system to be corrected to produce a corrected output. With the embodiments of the present disclosure, the nonlinear characteristic of the system to be measured under different inputs and/or parameters may be estimated, and accuracy of the estimation and applicability are improved.

Embodiments of the present invention provide a signal receiving method and a receiver. The signal receiving method includes: sequentially preprocessing a received first signal to obtain to-be-processed second signals; generating filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and filtering the corresponding second signals according to the filtering coefficients. Filtering can be performed according to different channel conditions and transmission requirements, thereby improving system performance of the receiver.

A femtocell telecommunication system equipment comprising: a base apparatus structured to provide a first information signal and control signals; an electrical conductor based transmission line connected to said base apparatus; a bidirectional conversion apparatus adapted to receive/transmit from/on the transmission line the first signal and the control signals; the bidirectional apparatus comprising: a processing module structured to process the first signal to generate a second information signal and vice-versa; the second signal being adapted to be transmitted/received by an antenna device connectable to the bidirectional apparatus.

Interference mitigation in SSB and/or TRS processing is described. An apparatus is configured to receive, from a network node, a reference signal associated with the network node and at least one neighboring network node. The apparatus is configured to obtain Rnn information from at least one noise tap of a CIR of the reference signal. The apparatus is also configured to apply a noise whitening to the CIR based on the Rnn information.

A wireless communication device is provided. The wireless communication device includes: a communication circuit configured to transceive a signal using a plurality of antennas; a processor configured to: detect a first interference for N resource blocks (RB) of the signal; based on the first interference being detected, perform a first whitening validation on the first interference; detect a second interference based on a result of the first whitening validation; and based on the second interference being detected, perform a second whitening validation on the second interference; and a whitening filter circuit configured to perform whitening filtering on results of the first whitening validation and the second whitening validation.

A wireless communication device includes a transceiver configured to receive a wireless signal, and a processor configured to in a time-frequency domain, in which resources are allocated across subcarriers and symbols in a given time slot for data transmission, determine a first area and a second area within a resource element (RE) area including a plurality of REs, segment the second area into a plurality of segmentation areas, calculate a first adjustment whitening filter and a plurality of segmentation adjustment whitening filters to be respectively applied to the first area and the plurality of segmentation areas, and perform an interference whitening operation on the first area and the plurality of segmentation areas, based on the first adjustment whitening filter and the plurality of segmentation adjustment whitening filters, respectively.

Provided are a communication processor and an operating method of the communication processor. The communication processor includes: a signal processing circuitry configured to perform an interference whitening operation for a receive signal, and perform a symbol detection operation and a channel decoding operation for the receive signal to output bit data, a controller configured to control the signal processing circuitry and receive channel state information for the receive signal or interference estimation data input from the outside, and an anomaly detection module configured to perform an interference detection operation based on the receive signal to determine whether to perform the interference whitening operation.

Devices, methods and computer programs for reducing complexity of a machine learning (ML) model-based radio receiver are disclosed. At least some example embodiments may allow, for example, reducing the number of computation operations, the size of data buffers, and/or the amount of data transferred for inference processing.